At its “Lab to Impact” dialogue, held alongside the India AI Impact Summit 2026, Google announced a fresh wave of collaborations and funding to turn India’s AI research into real-world impact across healthcare, agriculture, education and sustainability. The initiatives span digital public infrastructure, open models for Indic languages, and large-scale climate action—positioning India as both a testbed and export hub for AI solutions built for the Global South.
Dr Manish Gupta, Senior Research Director at Google DeepMind, underscored three shifts driving this strategy: AI accelerating scientific discovery, augmenting human capability, and India’s distinctive, large-scale embrace of AI’s potential. The company’s “full-stack” approach links foundational research, ecosystem partnerships and deployment at population scale, with the ambition that innovations from Indian labs benefit billions worldwide.
Building India’s Health Foundation Models and DPI
To advance AI in public health, Google is committing 400,000 USD to support the development of India’s Health Foundation Models using MedGemma. Ajna Lens will collaborate with experts from AIIMS to train models tailored to India-specific dermatology and OPD triage use cases, with outputs designed to plug into the country’s digital public infrastructure for health. Researchers and clinicians from IISc will also explore broader clinical applications, extending the models’ utility across specialties.
In parallel, Google is working with the National Health Authority to convert millions of fragmented, unstructured medical records—such as clinicians’ notes—into the global FHIR standard using advanced AI. The shift from free text to structured, machine-readable records aims to ease documentation burdens, improve patient understanding of their own health data, and give policymakers cleaner, more reliable datasets for public health planning. Google will also help bring over 400,000 NHA-registered health facilities—hospitals, clinics and diagnostic labs—onto Maps and Search so people can find verified, up-to-date information on nearby care options.
Funding AI Centres of Excellence and Indic Language Research
Over the past five years, Google has supported roughly 1,000 years of PhD-level research work across more than 25 Indian institutions, backing 166 Indian PhD students through its global fellowship programme. Building on this, Google.org is now providing 8 million USD to four government-backed AI Centres of Excellence aligned with the “Make AI in India, Make AI Work for India” vision. TANUH at IISc will target non-communicable diseases, Airawat at IIT Kanpur will focus on AI for urban governance, IIT Madras’ AI CoE for Education will work on learning and teaching outcomes, and ANNAM.AI at IIT Ropar will build data-driven solutions for agriculture and farmer welfare.
To deepen India’s strength in multilingual AI, Google is also making a 2 million USD founding contribution to create the Indic Language Technologies Research Hub at IIT Bombay, in memory of Professor Pushpak Bhattacharyya. The hub will focus on ensuring that frontier AI models and tools work effectively across India’s diverse languages, from foundational NLP research to applied solutions that make public services, education and content more accessible to non-English speakers.
Open Models, Startups and Developer Ecosystem
Indian startups are already tapping Google’s Gemma models for Indic Voice AI and citizen-facing services. To accelerate this, Google is awarding 50,000 USD each to Gnani.AI and CoRover.AI to scale voice and e-governance models for Indian languages, and another 50,000 USD grant to IIT Bombay to use Gemma for processing Indic health governance and policy documents—building an “India-centric trait database” of disease, phenotype and genetic insights.
To broaden access, Google has uploaded all 22 Gemma models to AIKosh, the IndiaAI Mission’s open data and model platform. This move is aimed at helping Indian developers and startups rapidly build indigenous models and applications without prohibitive infrastructure costs, turning AIKosh into a shared foundation for “Make in India” AI innovation across sectors.
Empowering Frontline Changemakers With AI
On the ground, Google’s open tools are already powering large-scale social solutions. Using Google’s Open Health Stack, non-profit Khushi Baby has delivered more than 35 million tuberculosis screenings in Rajasthan this year alone via an AI-enabled active case finding module aligned with India’s digital health mission and TB elimination goals. Research suggests AI-powered digital tools could significantly boost productivity for over one million ASHA workers, enabling tens of millions of additional visits annually and saving households billions of rupees in out-of-pocket health costs.
To scale such impact, Google.org is providing 2.5 million USD to Wadhwani AI to pilot HealthVaani, an LLM-based, multimodal, multilingual AI assistant that supports ASHA and Anganwadi workers in partnership with the Health and Women & Child Development ministries. A further 2 million USD grant will help Wadhwani AI build Garuda, a new Indian language model for agriculture that powers AgriVaani, a smartphone app offering farmers precise, context-aware advice on crops, livestock, pest detection and climate-smart practices.
Powering AI Growth With Clean Energy
Recognising that AI’s expansion must be sustainable, Google is partnering with ReNew Energy on a new 150 MW solar project in Rajasthan under a long-term agreement. Google will receive environmental attribute certificates from the project and allocate them to its value chain emissions, while also engaging key suppliers to adopt more clean energy. The aim is to create a replicable pathway for organisations to credibly address AI-related Scope 3 emissions, even when full supply-chain transparency is still evolving.
This builds on earlier collaborations with Adani Group and Clean Max that have already added 186 MW of wind and solar to India’s grid. Together, these investments support India’s target of 500 GW of non-fossil electricity capacity by 2030 and signal a model where AI leadership is underpinned by both social impact at scale and verifiable progress on decarbonisation.
